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    Home / Central Data Catalog / NUHDSS / APHRC-NUHDSS-HOUSEHOLD-AMENITIES-AND-LIVELIHOODS-1.2
NUHDSS

NUHDSS-Household Amenities and characteristics Information for All Households 2002-2015

KENYA, 2002 - 2015
Nairobi Urban Health & Demographic Surveillance System
African Population and Health Research Center
Last modified January 26, 2021 Page views 421667 Documentation in PDF Metadata DDI/XML JSON
  • Study description
  • Documentation
  • Data Description
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  • Related Publications
  • Identification
  • Version
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data Collection
  • Data Processing
  • Data access
  • Disclaimer and copyrights
  • Metadata production

Identification

IDNO
APHRC-NUHDSS-HOUSEHOLD-AMENITIES-AND-LIVELIHOODS-1.2
Title
NUHDSS-Household Amenities and characteristics Information for All Households 2002-2015
Country
Name Country code
KENYA KEN
Abstract
Under the NUHDSS the households are visited in two informal settlements in Nairobi every four months to collect information on health and other related issues so that we can understand the health and well-being of members of these communities. Specifically, we would like to know a bit about the nature of amenities and facilities as well as the household income, expenditure and the coping strategies that households have in case of a problem.

Version

Version Date
2015-12-31
Version Notes
Version 1.1, November 2014. Anonymized datasets with DOI and Recommended Citation added.

Version 1.2, February 2017.Datasets from 2002 to 2015

Coverage

Geographic Coverage
Two informal settlements (slums) in Nairobi county, Kenya (specifically, Korogocho and Viwandani slums).
Unit of Analysis
All households
Universe
The survey covers all the households in the DSA

Producers and sponsors

Authoring entity/Primary investigators
Agency Name Affiliation
African Population and Health Research Center APHRC
Funding Agency/Sponsor
Name Abbreviation Role
Wellcome Trust Funder
Rockefeller Foundation (USA) Funder
William and Flora Hewlett Foundation (USA) Funder
Comic Relief (UK) Funder
Swedish International Development Cooperation SIDA Funder
The Bill and Melinda Gates Foundation (USA) Funder
Other Identifications/Acknowledgments
Name Role
Residents of Korogocho and Viwandani Slums Study Subjects
Community leaders - chiefs and village elders Support to field teams

Sampling

Sampling Procedure
No sampling was done, all the households in the DSA were interviewed

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date Cycle
2002-08-01 2002-12-20 Round 0 and Round 1
2003-01-13 2003-12-19 Round 2, Round 3 and Round 4
2004-01-12 2004-12-22 Round 5, Round 6 and Round 7
2005-01-10 2005-11-18 Round 8, Round 9 and Round 10
2006-01-09 2006-12-22 Round 11, Round 12 and Round 13
2007-01-08 2007-12-21 Round 14, Round 15 and Round 16
2008-01-07 2008-12-19 Round 17 and Round 18
2009-01-05 2009-12-18 Round 19, Round 20 and Round 21
2010-01-04 2010-12-17 Round 22, Round 23 and Round 24
2011-01-03 2011-12-22 Round 25, Round 26 and Round 27
2012-01-09 2012-12-21 Round 28, Round 29 and Round 30
2013-01-07 2013-12-20 Round 31 and Round 32
2014-01-06 2014-12-19 Round 33, Round 34 and Round 35
2015-01-05 2015-12-21 Round 37 and Round 38
Mode of data collection
Face-to-face [f2f]
Supervision
Interviewing teams in the two sites of study comprised of:

- Korogocho: 1 field supervisor, 2 editting team leaders, 1 data quality control team leader, 1 deaths' monitoring team leader, 2 data quality control officers, 12 interviewers

- Viwandani: 1 field supervisor, 2 editting team leaders, 1 data quality control team leader, 1 deaths' monitoring team leader, 3 data quality control officers, 17 interviewers



The roles of the various members of the interviewing teams were:

- Interviewer: Conducting face-to-face paper-based interviews(Round 0- Round 38) and using Netbooks (Round 39 onwards) in assigned zone within the study site

- Data Quality Control Officer: Performing random spot-checks on 10% of the questionnaires and reporting inconsistencies to the Data Quality Control Team Leader for harmonization

within the study community

- Data Quality Control Team Leader: Harmonizing inconsistencies within questionnaires and performing a random spot-check on 10% of the 10% questionnaires that have already undergone spot-checking

- Editting Team Leader: Editting 100% of questionnaires from randomly selected field workers and documenting issues emerging during data collection

- Field supervisor: Responsible for overseeing general operations, resolving issues that cannot be harmonized by data quality control and ensuring that field work progressed on schedule. They also conducted sit-in interviews along with Data Quality Control Team Leader



The Field Co-ordinator, Research Officer and/or Project Managers visited the field and field teams regularly to monitor and review progress and support field operations.
Type of Research Instrument
1.Census questionnaire

2.Household amenities and livelihoods

3.Household characteristics form

Data Processing

Cleaning Operations
Data editing took place at a number of stages throughout the processing, including:

1. Quality control through back-checks on 10 percent of completed questionnaires and editing of all completed questionnaires by supervisors and project management staff.

2. A quality control officer performed internal consistency checks for all questionnaires and edited all paper questionnaires coming from the field before their submission for data entry with return of incorrectly filled questionnaires to the field for error-resolution.

3. During data entry, any questionnaires that were found to be inconsistent were returned to the field for resolution.

4. Data cleaning and editting was carried out using STATA Version 13 software.





Detailed documentation of the editing of data can be found in the "Standard Procedures Manual" document provided as an external resource.



Some corrections are made automatically by the program (80%) and the rest by visual control of the questionnaire (20%).



Where changes are made by the program, a cold deck imputation is preferred; where incorrect values are imputed using existing data from another dataset. If cold deck is found to be insufficient, hot deck imputation is used. In this case, a missing value is imputed from a randomly selected similar record in the same dataset.
Other Processing
Data were entered as follows:

1. Typed based on paper questionnaires at APHRC's headquarters on desktop computers. Double data entry was carried out on 10% of the questionnaires (Round 0- Round 38).

2. Using Netbooks (Round 39 onwards).



In both cases, data were captured using in-house software developed with a Visual Basic. Net front-end and a Microsoft Structured Query Language (SQL) Server back-end.

Data access

Contact
Name Email
Head, Data and Measurement Unit datarequests@aphrc.org
Conditions
All non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research. This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners/collaborators/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:

1. Data Ownership: The data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.

2. Purpose: The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.

3. Respondent Identifiers: The Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.

4. Confidentiality pledge: The user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.

5. Reporting of errors or inconsistencies: The user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.

6. Publications resulting from APHRC data: The Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.

7. Security: The user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.

8. Loss of privilege to use data: In the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.

9. Acknowledgement: Any work/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is:

"This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City."

Additionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.

10. Deposit of Reports/Papers: The user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.

11. Change of contact details: The user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.
Citation requirement
African Population and Health Research Center, Nairobi Urban Health and Demographic Surveillance System - Household Amenities and Livelihood Survey, February 2017. APHRC, Nairobi - Kenya. doi:10.20369/aphrc-011:2003.1.01

Disclaimer and copyrights

Disclaimer
The user of the data acknowledges that APHRC and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
Copyright © APHRC, 2017

Metadata production

Document ID
APHRC-NUHDSS-HOUSEHOLD-AMENITIES-AND-LIVELIHOODS-1.2
Producers
Name Abbreviation Role
African Population & Health Research Center APHRC Metadata Producer
Date of Production
2011-03-24
Document version
Version 1.2, FEBRUARY 2017
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